Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-20 are pending.
Claims 1, 7 and 15 are amended. No claims are added or cancelled.
Response to Arguments
Applicant's arguments filed with respect to Section 101 have been fully considered but they are not persuasive. As an initial matter, Applicant argues that the claims, as amended, are not directed to an abstract idea under Step 2A, Prong 1, because a person cannot mentally generate vector embeddings of IP assets, compute distances within an aggregated vector space, or cluster IP assets based on vector representations. However, the broadly recited vectorization process of the claims is not limited to certain large data sets as asserted in the arguments. The PTAB has stated, in an application with claims of similar complexity, that “the document embedding process is too complicated to be performed in the human mind … both for lack of sufficient evidence in support of the argument and because Appellant fails to identify any claim limitations requiring the alleged high level of complexity that is beyond a mental process. See, e.g., MPEP § 2106.04(a)(2)(III)(B) (“The use of a physical aid (e.g., pencil and paper or a slide rule) to help perform a mental step (e.g., a mathematical calculation) does not negate the mental nature of the limitation, but simply accounts for variations in memory capacity from one person to another.”).” See Appeal 2024-001258, Application 16/876,885. Further, the recited steps are not a technological solution. Rather, than some inventive process, paragraphs [0054], [0062], [0094], and [0115] of the specification each state “Techniques to generate vectors representing IP assets may include vectorization techniques such as Doc2Vec, or other similar techniques.” That is, Applicants disclosure relies on a technique originally discussed in “Document Embedding with Paragraph Vectors” by Dai et al. in 2015. As such, the claims may use the long known Doc2Vec technique in its intended manner for its intended purpose. As such, the claims recited the use of technology to perform an abstract idea, not any technological solution to a technological problem.
Applicant further argues that the claims are integrated into a practical application under Step 2A, Prong 2. These elements are not generic computer components performing generic functions. Again, as noted above, the specification indicates that the long known Doc2Vec technique and nothing other than generic computer components. The claims are also not limited to large sets of data as asserted by Applicants. As such, the arguments are not persuasive. The rejection has been updated to address the amended claims.
Applicant’s arguments with respect to Section 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. §101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) with no practical application and without significantly more. Under MPEP 2106, when considering subject matter eligibility under 35 U.S.C. § 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (step 1). If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea) (step 2A prong 1), and if so, it must additionally be determined whether the claim is integrated into a practical application (step 2A prong 2). If an abstract idea is present in the claim without integration into a practical application, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself (step 2B).
In the instant case, claims 1-20 are directed to a method and system. Thus, each of the claims falls within one of the four statutory categories (step 1).
Under Step 2A Prong 1, the test is to identify whether the claims are "directed to" a judicial exception. Examiner notes that the claimed invention is directed to an abstract idea in that the instant application is directed to certain methods of organizing human activity specifically commercial interactions and behaviors and managing personal behavior and/or interactions between people (see MPEP 2106.04(a)(2)(II)), mental processes (see MPEP 2106.04(a)(2)(III), and mathematical equations (see MPEP 2106.04(a)(2)(II)).
Representative claim 1 recites “
identifying a first entity having first intellectual property (IP) assets; generating first vectors representing the first IP assets, the first vectors corresponding to a lower dimensional representation of the first IP assets; generating an aggregated vector space that includes at least the vectors; utilizing the aggregated vector space to determine, for individual ones of the second IP assets, a distance between the first vectors and the second vectors within the aggregated vector space, the distance indicating a degree of similarity between the first IP assets and the individual ones of the second IP assets; generating … second entities having second IP assets that are similar to one or more of the first IP assets, wherein similarity of the second IP assets is determined based at least in part on the distance between the first vectors and the second vectors within the aggregated vector space of the second IP assets; and …; receiving, via the GUI, first input data representing the input, the first input data indicating selection of at least one of the second entities as selected entities and a first time period; generating, based at least in part on the second IP assets associated with the selected entities, first filtered data representing a first filtered result set including at least: a first cluster including a first filtered portion of the second IP assets associated with the selected entities, the first cluster generated based at least in part on the second vectors of the second IP assets within the aggregated vector space; and a first metric associated with the second IP assets included in the first filtered portion, wherein the first metric is generated utilizing a machine learning model specifically trained to assess a quality of IP assets; …; generating, based at least in part on the second IP assets associated with the selected entities and the second time period, second data representing a second filtered result set including at least one of: a second cluster including a second portion of the second IP vectors assets associated with the selected entities; a second metric associated with the second IP assets included in the first filtered portion, wherein the second metric is generated utilizing the machine learning model specifically trained to assess the quality of IP assets; or a new IP asset added to the first cluster; and ….”. Examiner notes that the claimed invention is directed to concepts that are performed mentally and a product of human mental work. Because the limitations above closely follow the steps of processing information related to market information associated to quantified technology, and the steps involved human judgments, obs1ervations and evaluations that can be practically or reasonably performed in the human mind, the claim recites an abstract idea consistent with the "mental process" grouping set forth in the see MPEP 2106.04(a)(2)(III). Alternatively, Examiner notes that claims 1-20 recite a processing and displaying information related to intellectual property assets, and is similar to the abstract idea identified in MPEP 2106.04(a)(2)(II) in grouping "II" in that the claims recite certain methods of organizing human activity such as organizing human activity of fundamental economic activities, legal/business interactions and risk management (i.e., technology/asset analyzing, valuing, processing, and protecting). This is merely further embellishments of the abstract idea and does not further limit the claimed invention to render the claims patentable subject matter. The limitations, substantially comprising the body of the claim, recite standard processes found in standard practice in intellectual property management. This is common practice when IP creation, production, prosecution, litigation, and management of IP assets and technology. For example, such vectorizations may be as simple as assigning or even simply reading classifications assigned to or referenced by an application.
Because the limitations above closely follow the steps standard in interactions between people and businesses such as technology/asset analyzing, valuing, processing, and protecting), and the steps of the claims involve organizing human activity, the claim recites an abstract idea consistent with the "organizing human activity" grouping set forth in the see MPEP 2106.04(a)(2)(II). Furthermore, the claims recite the familiar concept of property valuation. As the Supreme Court explained in Alice, claims involving "a fundamental economic practice long prevalent in our system of commerce," such as the concepts of hedging and inter-mediated settlement, are patent-ineligible abstract ideas. Alice, 134 S. Ct. at 2356 (quoting Bilski V. Kappos, 561 U.S. 593, 611 (2010)). It follows that the claims at issue here are directed to an abstract idea. Applicants' claims recite one or more computers configured to receive a user's property valuations, and display that information. Like the risk hedging in Bilski and the concept of intermediated settlement in Alice, the concept of property valuation, that is, determining a property's market value, is "a fundamental economic practice long prevalent in our system of commerce." Id. (quoting Bilski, 561 U.S. at 611). Prospective sellers and buyers have long valued property and doing so is necessary to the functioning of the residential real estate market. As such, claim 1 is directed to the abstract idea of “intellectual property valuation” and is similar to the abstract idea identified in MPEP 2106.04(a)(2)(II) in grouping "II" in that the claims recite certain methods of organizing human activity such as fundamental economic practices. This is merely further embellishments of the abstract idea and docs not further limit the claimed invention to render the claims patentable subject matter. The limitations, substantially comprising the body of the claim, recite standard processes found in standard practice in intellectual property creation, valuation, protection, and management. This is common practice when creating and protecting any intellectual property. Because the limitations above closely follow the steps standard in fundamental economic practices such as process valuation, and the steps of the claims involve organizing human activity, the claim recites an abstract idea consistent with the "organizing human activity" grouping set forth in the see MPEP 2106.04(a)(2)(II).
The conclusion that the claim recites an abstract idea within the groupings of the MPEP 2106.04(a)(2) remains grounded in the broadest reasonable interpretation consistent with the description of the invention in the specification. For example, [App. Spec 3], "an intellectual property landscaping platform". Accordingly, the Examiner submits claims 1-20, recite an abstract idea based on the language identified in claim 1, 7, and 15, and the abstract ideas previously identified based on that language that remains consistent with the groupings of Step 2A Prong 1 of the MPEP 2106.04(a)(1).
If the claims are directed toward the judicial exception of an abstract idea, it must then be determined under Step 2A Prong 2 whether the judicial exception is integrated into a practical application. Examiner notes that considerations under Step 2A Prong 2 comprise most the consideration previously evaluated in the context of Step 2B. The Examiner submits that the considerations discussed previously determined that the claim does not recite "significantly more" at Step 2B would be evaluated the same under Step 2A Prong 1 and result in the determination that the claim does not integrate the abstract idea into a practical application.
The instant application fails to integrate the judicial exception into a practical application
because the instant application amount to merely reciting the words "apply it" (or an equivalent) with the judicial exception or merely includes instructions to implement an abstract idea. The instant application is directed to a method instructing the reader to implement the identified method of organizing human activity of fundamental economic activities, legal/business interactions and risk management (i.e., technology/asset analyzing, valuing, processing, and protecting) on generically claimed computer structure. For instance, the additional elements or combination of elements other than the abstract idea itself include the elements such as generating a graphical user interface (GUI) configured to display on a computing device, the GUI configured to: display second entities having second IP assets that are similar to one or more of the first IP assets, receive an input from the computing device; receiving, via the GUI, second input data, the second input data indicating selection of at least a second time period; and causing the GUI to display at least one of the first filtered result set or the second filtered result set, and in other independent claims further additional elements such as "interface", "processor", "machine learning model", and "memory" recited at a high level of generality. These elements do not themselves amount to an improvement to the interface or computer, to a technology or another technical field. This is consistent with Applicant's disclosure which states that “Techniques to generate vectors representing IP assets may include vectorization techniques such as Doc2Vec, or other similar techniques.” (App. Spec. 20) and "The user interface(s) 114 may be configured to display information associated with the IP landscaping platform and to receive user input associated with the IP landscaping platform. [00100] The remote computing resources 104 may include one or more components such as, for example, one or more processors 116, one or more network interfaces 118, and/or computer-readable media 120. The computer-readable media 120 may include one or more components, such as, for example, a landscaping component 122, an scoring component 124, and/or one or more data store(s) 126.". (App. Spec. 99).
Accordingly, the claimed "system" read in light of the specification employs any wide range of possible devices comprising a number of components that are generically recited commercially available technical elements. and included in an indiscriminate "interface", "processor", "machine learning model", and "memory" (e.g., processing device, modules). Thus, the claimed structure amounts to appending generic computer elements to abstract idea comprising the body of the claim. The computing elements are only involved at a general, high level, and do not have the particular role within any of the functions but to be a computer-implemented method using a generically claimed "interface", "processor", and "memory" and even basic, generic recitations that imply use of the computer such as storing information via servers would add little if anything to the abstract idea. Similarly, reciting the abstract idea as software functions used to program a generic computer is not significant or meaningful: generic computers are programmed with software to perform various functions every day. A programmed generic computer is not a particular machine and by itself does not amount to an inventive concept because, as discussed in MPEP 2106.05(a), adding the words "apply it" (or an equivalent) with the judicial exception, or more instructions to implement an abstract idea on a computer, as discussed in Alice, 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)), is not enough to integrate the exception into a practical application. Further, it is not relevant that a human may perform a task differently from a computer. It is necessarily true that a human might apply an abstract idea in a different manner from a computer. What matters is the application, "stating an abstract idea while adding the words 'apply it with a computer" will not render an abstract idea non-abstract. Tranxition V. Lenovo, Nos. 2015-1907, -1941, -1958 (Fed. Cir. Nov. 16, 2016), slip op. at 7-8.
Here, the instructions entirely comprise the abstract idea, leaving little if any aspects of the claim for further consideration under Step 2A Prong 2. In short, the role of the generic computing elements recited in claim 1, 7, and 15, is the same as the role of the computer in the claims considered by the Supreme Court in Alice, and the claim as whole amounts merely to an instruction to apply the abstract idea on the generic computerized system. Therefore, the claims have failed to integrate a practical application (2106.04(d)). Under the MPEP 2106.05, this supports the conclusion that the claim is directed to an abstract idea, and the analysis proceeds to Step 2B.
While many considerations in Step 2A need not be reevaluated in Step 2B because the outcome will be the same. Here, on the basis of the additional elements other than the abstract idea, considered individually and in combination as discussed above, the Examiner respectfully submits that the claims 1, 7, and 15, do not contain any additional elements that individually or as an ordered combination amount to an inventive concept and the claims are ineligible.
With respect to the dependent claims do not recite anything that is found to render the abstract idea as being transformed into a patent eligible invention. The dependent claims are merely reciting further embellishments of the abstract idea and do not claim anything that amounts to significantly more than the abstract idea itself.
Claims 2-6, 8-14, and 16-20 are directed to further embellishments of the abstract idea in that they are directed to aspects of the intellectual property information processing which is the central theme of the abstract idea identified above, as well as being directed to data processing and transmission which the courts have recognized as insignificant extra-solution activities (see at least M.P.E.P. 2106.05(g)). Data transmission is one of the most basic and fundamental uses there are for a generic computing device is not sufficient to amount to significantly more. The examiner takes the position that simply appending the judicial exception with such a well understood step of data transmission is not going to amount to significantly more than the abstract idea.
Therefore, since there are no limitations in the claim that transform the abstract idea into a patent eligible application such that the claim amounts to significantly more than the abstract idea itself, the claims are rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter. See MPEP 2106.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 1, 5-7, 11-15, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No. 11232383 to Burns et al. in view of U.S. Patent Application Publication No. 20220172502 to Liberty et al.
Referring to Claim 1 and 7 (substantially similar in scope and language), Burns discloses a method comprising:
identifying a first entity having first intellectual property (IP) assets (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3);
…
generating a graphical user interface (GUI) configured to display on a computing device, the GUI configured to: display second entities having second IP assets that are similar to one or more of the first IP assets (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; sec also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development); and
receive an input from the computing device; receiving, via the GUI, first input data representing the input, the first input data indicating selection of at least one of the second entities as selected entities and a first time period (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development);
generating, based at least in part on the second IP assets associated with the selected entities, first filtered data representing a first filtered result set including at least: a first cluster including a first filtered portion of the second IP … assets associated with the selected entities (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development); and
a first metric associated with the second IP assets included in the first filtered portion, wherein the first metric is generated utilizing a machine learning model specifically trained to assess a quality of IP assets (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development; see also Burns: Col. 28 Line 1-13, Col. 33 Line 5-16, Col. 39 Line 23-56, Col. 42 Line 6-25, Col. 50 Line 20-28, Col. 68 Line 10-65, and Col. 72 Line 1-28: all discussing the utilization of machine learning algorithms that are used to score the technology);
receiving, via the GUI, second input data, the second input data indicating selection of at least a second time period (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development);
generating, based at least in part on the second IP assets associated with the selected entities and the second time period, second data representing a second filtered result set including at least one of: a second cluster including a second portion of the second IP … assets associated with the selected entities a second metric associated with the second IP assets included in the first filtered portion, wherein the second metric is generated utilizing the machine learning model specifically trained to assess the quality of IP assets; or a new IP asset added to the first cluster;(see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development);
a second metric associated with the second IP assets included in the first filtered portion, wherein the second metric is generated utilizing the machine learning model specifically trained to assess the quality of IP assets; or a new IP asset added to the first cluster; and causing the GUI to display at least one of the first filtered result set or the second filtered result set (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52, : discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development; see also Burns: Col. 28 Line 1-13, Col. 33 Line 5-16, Col. 39 Line 23-56, Col. 42 Line 6-25, Col. 50 Line 20-28, Col. 68 Line 10-65, and Col. 72 Line 1-28: all discussing the utilization of machine learning algorithms that are used to score the technology), but fails to explicitly teach generating first vectors representing the IP assets. However Liberty et al. teaches
generating first vectors representing the first IP assets, the first vectors corresponding to a lower dimensional representation of the first IP assets (paragraph [0036], “For each of the plurality of candidate patents, the computing system (1) retrieves the candidate patent from one of the one or more first data systems, (2) parses textual information of the candidate patent using the NLP engine, (3) extracts a set of features representing the parsed textual information of the candidate patent (hereinafter, also referred to as a second set of features), and (4) transforms the set of features into a feature vector (herein, also referred to as a second feature vector). Similar to the first feature vector, the second feature vector is a vector that has a plurality of dimensions, each of which corresponds to a value of a feature contained in the second set of features.”);
generating an aggregated vector space that includes at least the vectors (paragraph [0059], “As briefly discussed above, when the candidate patents are identified, each of the candidate patents is compared with the source patent. However, since the candidate patents and the source patent are fairly unstructured text documents, it is difficult to compare the two sets of textual information directly. In some embodiments, before the comparison is performed, a set of features is first extracted from each of the candidate patents and the source patent. A feature is a relevant parameter that can be used to describe a patent document. Each set of features may then be represented by an object (e.g., a vector) that has a predetermined data structure. The object represents the features of the source patent, and the objects represent the features of the candidate patents may then be compared to determine a similarity score.”);
utilizing the aggregated vector space to determine, for individual ones of the second IP assets, a distance between the first vectors and the second vectors within the aggregated vector space, the distance indicating a degree of similarity between the first IP assets and the individual ones of the second IP assets (paragraph [0106], “For example, the vector representing the word embedding of a target word can have one position (or dimension) for each word or phrase in the corpus, where the value of each position is the total count, relative frequency, or other measure of how frequently that word is collocated with the target word. Synonyms of a target word can then be identified as the group of words within a defined cosine distance from the target word, such as within a threshold, the top n words, or some other measure.”);
generating a graphical user interface (GUI) configured to display on a computing device, the GUI configured to: display second entities having second IP assets that are similar to one or more of the first IP assets (paragraph [0037], “The computing system then determines a similarity (e.g., generates a similarity score) between the first feature vector (representing the source patent) and the second feature vector (representing a candidate patent). Based on the similarity between the first feature vector and each second feature vector, the computing system identifies one or more target patents. For example, in some embodiments, when a similarity between the first feature vector and a second feature vector is greater than a predetermined threshold, the computing system determines that the candidate patent is a target patent.”), wherein similarity of the second IP assets is determined based at least in part on the distance between the first vectors and the second vectors within the aggregated vector space of the second IP assets (paragraph [0063], “A vector representing the source patent can then be compared with a vector representing a target candidate patent. A similarity between the two vectors may then be calculated. Different embodiments (e.g., cosine similarity, Euclidean distance, dot product) may be implemented to calculate similarities between two vectors. In some embodiments, once the source patent and a plurality of candidate patents are identified, a set of features are extracted from each of the source patent and the plurality of candidate patents, and each set of the features is transformed to a vector. The vector representing the source patent is compared to each vector representing each candidate patent to determine a similarity score. In some embodiments, when the similarity score is greater than a predetermined threshold, the candidate patent is identified as a target patent. In some embodiments, a predetermined number of candidate patents that have the highest similarity scores are identified as a target patent.”); and
generating, based at least in part on the second IP assets associated with the selected entities, first filtered data representing a first filtered result set including at least (paragraph [0037], “Based on the similarity between the first feature vector and each second feature vector, the computing system identifies one or more target patents. For example, in some embodiments, when a similarity between the first feature vector and a second feature vector is greater than a predetermined threshold, the computing system determines that the candidate patent is a target patent.”):
a first cluster including a first filtered portion of the second IP assets associated with the selected entities, the first cluster generated based at least in part on the second vectors of the second IP assets within the aggregated vector space (paragraph [0063], “These structured objects (e.g., lists or matrixes) may also be called and treated as vectors. For example, each word in the dictionary may be deemed as a separate dimension. A vector representing the source patent can then be compared with a vector representing a target candidate patent. A similarity between the two vectors may then be calculated. Different embodiments (e.g., cosine similarity, Euclidean distance, dot product) may be implemented to calculate similarities between two vectors. In some embodiments, once the source patent and a plurality of candidate patents are identified, a set of features are extracted from each of the source patent and the plurality of candidate patents, and each set of the features is transformed to a vector. The vector representing the source patent is compared to each vector representing each candidate patent to determine a similarity score. In some embodiments, when the similarity score is greater than a predetermined threshold, the candidate patent is identified as a target patent.”); and
a first metric associated with the second IP assets included in the first filtered portion, wherein the first metric is generated utilizing a machine learning model specifically trained to assess a quality of IP assets (paragraph [0091], “Next, the patent matching analysis system then searches based on the selected patent family class into the target patent system and generates one or more sets of pairings, selects target patents (which may also be referred to as candidate patents), and determine closeness factor for a next process (act 1240). The act 1240 may repeat as many times as necessary to identify closer target patents. The target patents (i.e., candidate patents) are then analyzed to select closer target patents (act 1250).”);
generating, based at least in part on the second IP assets associated with the selected entities and the second time period, second data representing a second filtered result set including at least one of: a second cluster including a second portion of the second IP vectors assets associated with the selected entities; a second metric associated with the second IP assets included in the first filtered portion, wherein the second metric is generated utilizing the machine learning model specifically trained to assess the quality of IP assets; or a new IP asset added to the first cluster (paragraph [0063], “The vector representing the source patent is compared to each vector representing each candidate patent to determine a similarity score. In some embodiments, when the similarity score is greater than a predetermined threshold, the candidate patent is identified as a target patent. In some embodiments, a predetermined number of candidate patents that have the highest similarity scores are identified as a target patent.”); and
causing the GUI to display at least one of the first filtered result set or the second filtered result set (paragraph [0071] “As shown in FIG. 5, the taxonomy system 500 classifies the patents in categories in different hierarchies. How many categories (i.e., the granularity of the categories) are to be used or presented to a user may be customized by a user or determined by the hierarchical classifier 460. For example, a user may define that patents contained in each category must have a similarity score higher than a predetermined threshold. In such a case, a line (e.g., a dotted line 520) may be drawn at a height that represents the predetermined threshold of similarity score.”).
This part of Liberty et al. is applicable to the system of Burns et al. as they both share characteristics and capabilities, namely, they are directed to IP documentation analysis . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Burns et al. to include the vector analysis as taught by Liberty et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Burns et al. in order to improve analysis of patents and/or court documents and identifying matching and/or related patents with greater efficiency (see paragraphs [0003]-[0007] of Liberty et al.).
Referring to Claim 5, Burns discloses the method of claim 1 wherein at least one of the first metric or the second metric include a coverage metric, an opportunity metric, and an exposure metric (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; sec also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Linc 25-55, Col. 52 Line 29-52, : discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development).
Referring to Claim 6, Burns discloses the method of claim 1, wherein at least one of the first metric or the second metric includes a comprehensive metric based at least in part on a coverage metric, an opportunity metric, and an exposure metric (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52, : discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development).
Referring to Claim 11, Burns discloses the method of claim 7, wherein the metric associated with the first cluster indicates at least one of: geographical data; breadth data; expiration data; diversity data; revenue alignment data; invalidity data; filing velocity data; spending data; predictive analytics data; precedence data; litigation data; market data; or revenue alignment data (see at least Burns: Col. 41 Linc 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52, : discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development).
Referring to Claim 12, Burns discloses the method of claim 7, further comprising displaying at least one of a coverage metric, an opportunity metric, an exposure metric, or a comprehensive metric in response to a selection of at least one IP asset displayed on a first portion of the GUI (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52, : discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development).
Referring to Claim 13, Burns discloses the method of claim 12, wherein displaying the
at least one of the coverage metric, the opportunity metric, the exposure metric, or the comprehensive metric in response to the selection of the at least one IP asset displayed on the
first portion of the GUI comprises displaying an information overly window within the first portion of the GUI (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; sec also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development).
Referring to Claim 14, Burns discloses the method of claim 1, further comprising:
identifying, from the second IP assets, foreign IP assets and design IP assets as third IP assets; and removing the third IP assets from the second IP assets prior to generating data representing the first result set and the second result set (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development).
Referring to Claim 15, Burns discloses a system comprising: one or more processors; and one or more non-transitory computer-readable media comprising instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
identifying a first entity having first intellectual property (IP) assets; and generating a graphical user interface (GUI) configured to display on a computing device (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; sec also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3), the GUI configured to: display second entities having second IP assets that are similar to one or more of the first IP assets ….; and receive an input from the computing device (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development);
receiving, via the GUI, first input data representing the input, the first input data indicating selection of at least one of the second entities as selected entities and a first time period (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Linc 27-59 and Col. 78 Line 1-3; sec also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development);
generating, based at least in part on the second IP assets associated with the selected entities, first filtered data representing a first filtered result set including a first cluster including a first filtered portion of the second IP … assets associated with the selected entities, the first filtered result set being associated with a first period of time (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development);
receiving, via the GUI, second input data, the second input data indicating selection of at least a second time period (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development);
generating, based at least in part on the second IP assets associated with the selected entities and the second time period, second data representing a second filtered result set indicating a change to the first filtered result set, wherein the change to the first result set includes at least one of: a second cluster including a second portion of the second IP … assets associated with the selected entities; a change to a metric associated with the first cluster wherein the metric is generated utilizing a machine learning model specifically trained to assess a quality of IP assets; a new IP asset added to the first cluster; or a removal of an IP asset from the first cluster; and causing the GUI to display at least one of the first filtered result set or the second filtered result set (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; sec also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64:
discussing and identifying disruptive innovation determination and development; see also Burns: Col. 28 Line 1-13, Col. 33 Line 5-16, Col. 39 Line 23-56, Col. 42 Line 6-25, Col. 50 Line 20-28, Col. 68 Line 10-65, and Col. 72 Line 1-28: all discussing the utilization of machine learning algorithms that are used to score the technology), but fails to explicitly teach generating first vectors representing the IP assets. However Liberty et al. teaches
generating first vectors representing the first IP assets, the first vectors corresponding to a lower dimensional representation of the first IP assets (paragraph [0036], “For each of the plurality of candidate patents, the computing system (1) retrieves the candidate patent from one of the one or more first data systems, (2) parses textual information of the candidate patent using the NLP engine, (3) extracts a set of features representing the parsed textual information of the candidate patent (hereinafter, also referred to as a second set of features), and (4) transforms the set of features into a feature vector (herein, also referred to as a second feature vector). Similar to the first feature vector, the second feature vector is a vector that has a plurality of dimensions, each of which corresponds to a value of a feature contained in the second set of features.”);
generating an aggregated vector space that includes at least the vectors (paragraph [0059], “As briefly discussed above, when the candidate patents are identified, each of the candidate patents is compared with the source patent. However, since the candidate patents and the source patent are fairly unstructured text documents, it is difficult to compare the two sets of textual information directly. In some embodiments, before the comparison is performed, a set of features is first extracted from each of the candidate patents and the source patent. A feature is a relevant parameter that can be used to describe a patent document. Each set of features may then be represented by an object (e.g., a vector) that has a predetermined data structure. The object represents the features of the source patent, and the objects represent the features of the candidate patents may then be compared to determine a similarity score.”);
utilizing the aggregated vector space to determine, for individual ones of the second IP assets, a distance between the first vectors and the second vectors within the aggregated vector space, the distance indicating a degree of similarity between the first IP assets and the individual ones of the second IP assets (paragraph [0106], “For example, the vector representing the word embedding of a target word can have one position (or dimension) for each word or phrase in the corpus, where the value of each position is the total count, relative frequency, or other measure of how frequently that word is collocated with the target word. Synonyms of a target word can then be identified as the group of words within a defined cosine distance from the target word, such as within a threshold, the top n words, or some other measure.”);
generating a graphical user interface (GUI) configured to display on a computing device, the GUI configured to: display second entities having second IP assets that are similar to one or more of the first IP assets (paragraph [0037], “The computing system then determines a similarity (e.g., generates a similarity score) between the first feature vector (representing the source patent) and the second feature vector (representing a candidate patent). Based on the similarity between the first feature vector and each second feature vector, the computing system identifies one or more target patents. For example, in some embodiments, when a similarity between the first feature vector and a second feature vector is greater than a predetermined threshold, the computing system determines that the candidate patent is a target patent.”), wherein similarity of the second IP assets is determined based at least in part on the distance between the first vectors and the second vectors within the aggregated vector space of the second IP assets (paragraph [0063], “A vector representing the source patent can then be compared with a vector representing a target candidate patent. A similarity between the two vectors may then be calculated. Different embodiments (e.g., cosine similarity, Euclidean distance, dot product) may be implemented to calculate similarities between two vectors. In some embodiments, once the source patent and a plurality of candidate patents are identified, a set of features are extracted from each of the source patent and the plurality of candidate patents, and each set of the features is transformed to a vector. The vector representing the source patent is compared to each vector representing each candidate patent to determine a similarity score. In some embodiments, when the similarity score is greater than a predetermined threshold, the candidate patent is identified as a target patent. In some embodiments, a predetermined number of candidate patents that have the highest similarity scores are identified as a target patent.”); and
generating, based at least in part on the second IP assets associated with the selected entities, first filtered data representing a first filtered result set including at least (paragraph [0037], “Based on the similarity between the first feature vector and each second feature vector, the computing system identifies one or more target patents. For example, in some embodiments, when a similarity between the first feature vector and a second feature vector is greater than a predetermined threshold, the computing system determines that the candidate patent is a target patent.”):
a first cluster including a first filtered portion of the second IP assets associated with the selected entities, the first cluster generated based at least in part on the second vectors of the second IP assets within the aggregated vector space (paragraph [0063], “These structured objects (e.g., lists or matrixes) may also be called and treated as vectors. For example, each word in the dictionary may be deemed as a separate dimension. A vector representing the source patent can then be compared with a vector representing a target candidate patent. A similarity between the two vectors may then be calculated. Different embodiments (e.g., cosine similarity, Euclidean distance, dot product) may be implemented to calculate similarities between two vectors. In some embodiments, once the source patent and a plurality of candidate patents are identified, a set of features are extracted from each of the source patent and the plurality of candidate patents, and each set of the features is transformed to a vector. The vector representing the source patent is compared to each vector representing each candidate patent to determine a similarity score. In some embodiments, when the similarity score is greater than a predetermined threshold, the candidate patent is identified as a target patent.”); and
a first metric associated with the second IP assets included in the first filtered portion, wherein the first metric is generated utilizing a machine learning model specifically trained to assess a quality of IP assets (paragraph [0091], “Next, the patent matching analysis system then searches based on the selected patent family class into the target patent system and generates one or more sets of pairings, selects target patents (which may also be referred to as candidate patents), and determine closeness factor for a next process (act 1240). The act 1240 may repeat as many times as necessary to identify closer target patents. The target patents (i.e., candidate patents) are then analyzed to select closer target patents (act 1250).”);
generating, based at least in part on the second IP assets associated with the selected entities and the second time period, second data representing a second filtered result set including at least one of: a second cluster including a second portion of the second IP vectors assets associated with the selected entities; a second metric associated with the second IP assets included in the first filtered portion, wherein the second metric is generated utilizing the machine learning model specifically trained to assess the quality of IP assets; or a new IP asset added to the first cluster (paragraph [0063], “The vector representing the source patent is compared to each vector representing each candidate patent to determine a similarity score. In some embodiments, when the similarity score is greater than a predetermined threshold, the candidate patent is identified as a target patent. In some embodiments, a predetermined number of candidate patents that have the highest similarity scores are identified as a target patent.”); and
causing the GUI to display at least one of the first filtered result set or the second filtered result set (paragraph [0071] “As shown in FIG. 5, the taxonomy system 500 classifies the patents in categories in different hierarchies. How many categories (i.e., the granularity of the categories) are to be used or presented to a user may be customized by a user or determined by the hierarchical classifier 460. For example, a user may define that patents contained in each category must have a similarity score higher than a predetermined threshold. In such a case, a line (e.g., a dotted line 520) may be drawn at a height that represents the predetermined threshold of similarity score.”).
This part of Liberty et al. is applicable to the system of Burns et al. as they both share characteristics and capabilities, namely, they are directed to IP documentation analysis . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Burns et al. to include the vector analysis as taught by Liberty et al. One of ordinary skill in the art before the effective filing date of the claimed invention would have been motivated to modify Burns et al. in order to improve analysis of patents and/or court documents and identifying matching and/or related patents with greater efficiency (see paragraphs [0003]-[0007] of Liberty et al.).
Referring to Claim 18, Burns discloses the system of claim 15, further comprising displaying at least one of a coverage metric, an opportunity metric, an exposure metric, or a comprehensive metric in response to a selection of at least one IP asset displayed on a first portion of the GUI (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development).
Referring to Claim 19, Burns discloses the system of claim 18, wherein displaying the at least one of the coverage metric, the opportunity metric, the exposure metric, or the comprehensive metric in response to the selection of the at least one IP asset displayed on the first portion of the GUI comprises displaying an information overly window within the first portion of the GUI (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected, analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Linc 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development).
Referring to Claim 20, Burns discloses the system of claim 15, further comprising: identifying, from the second IP assets, foreign IP assets and design IP assets as third IP assets; and removing the third IP assets from the second IP assets prior to generating data representing the first result set and the second result set (see at least Burns: Col. 41 Line 33-67 and Col. 42 Line 5-35; see at least Burns Cols. 52-54: discussing the plethora of information collected,
analyzed, quantified, and presented to users including market information; see also Burns: Col. 67-68: discussing the system quantifying a plurality of technologies and assets into a score and aggregating a plurality of scores to identify the potential success; see also Burns: Col. 50 Line 17-28; see also Burns: Col. 27 Line 20-55; see also Burns: Col. 56 Line 27-59 and Col. 78 Line 1-3; see also Burns: Cols. 61-62: discussing scoring ideas, patents, products, and services to known patents and publications; see also Burns: Col. 48 Line 1-40, Col. 49 Line 10-58, Col. 51 Line 25-55, Col. 52 Line 29-52: discussing phase 0 through 2 discussing the formulation, adjustment, and tailoring of solutions to technical challenges; see also Burns Col. 54, Col. 55 Line 15-67, Col. 63-64: discussing and identifying disruptive innovation determination and development).
Claim(s) 2-4, 8-10, and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No. 11232383 to Burns et al. and U.S. Patent Application Publication No. 20220172502 to Liberty et al. in view of U.S. Patent Application Publication No. 20100250340 to Lee et al. (hereinafter Lee).
Referring to Claim 2, 8, and 16 (substantially similar in scope and language), modified Burns discloses the method of claim 1 and claim 7, and the system of claim 15; modified Burns discloses displaying a plethora of information based on the inputs of users and generating the information in a single display of a plurality of layered information but fails to state further comprising receiving the selection of the first time period and the second time period via a slider mechanism.
However, Lee, which talks about a method and system for processing and displaying intellectual property information, teaches it is known to employ a slider mechanism to allow the user to adjust the time period in which data is being analyzed for display (see at least Lee: I 96"The global map 2440 includes a time control or time slider control that a user may manipulate. In response to user manipulation, an algorithm may access information germane to a query with respect to time and update the global map graphic accordingly"; see also Lee: 1 116 "The user interface 2600 allows a user to select a point in time via the time control 2650. A user may manipulate the slider or elect to automate the slider to move backward or forward in time"; see also Lee: 1 128 "FIG. 30 is a diagram of an actual time slider 3010 with three rows or columns where the length of the column changes upon placement of a cursor over the timeline 3010"; see also Lee: Claims 16-18).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of using a slider mechanism to control the display of specific patent information (as disclosed by Lee) to the known method and system for managing, analyzing, processing, and presenting intellectual property information wherein the system is capable of displaying a plethora of information based on the inputs of users and generating the information in a single display of a plurality of layered information (as disclosed by modified Burns) to provide understandable graphics, bookmarks, documents associated with codes and optionally other documents and/or graphics. One of ordinary skill in the art would have been motivated to apply the known technique of using a slider mechanism to control the display of specific patent information because it would provide understandable graphics, bookmarks, documents associated with codes and optionally other documents and/or graphics (see Lee Il 95).
Furthermore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of using a slider mechanism to control the display of specific patent information (as disclosed by Lee) to the known method and system for managing, analyzing, processing, and presenting intellectual property information wherein the system is capable of displaying a plethora of information based on the inputs of users and generating the information in a single display of a plurality of layered information (as disclosed by modified Burns) to provide understandable graphics, bookmarks, documents associated with codes and optionally other documents and/or graphics, because the claimed invention is merely applying a known technique to a known method ready for improvement to yield predictable results. See KSR Int 'I Co. V. Teleflex Inc., 550 U.S. 398, 406 (2007). In other words, all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results to one of ordinary skill in the art at the time of the invention (i.e., predictable results are obtained by applying the known technique of using a slider mechanism to control the display of specific patent information to the known method and system for managing, analyzing, processing, and presenting intellectual property information wherein the system is capable of displaying a plethora of information based on the inputs of users and generating the information in a single display of a plurality of layered information to provide understandable graphics, bookmarks, documents associated with codes and optionally other documents and/or graphics). See also MPEP § 2143(I)(D).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of using a slider mechanism to control the display of specific patent information (as disclosed by Lee) to the known method and system for managing, analyzing, processing, and presenting intellectual property information wherein the system is capable of displaying a plethora of information based on the inputs of users and generating the information in a single display of a plurality of layered information (as disclosed by modified Burns) to provide understandable graphics, bookmarks, documents associated with codes and optionally other documents and/or graphics. One of ordinary skill in the art would have been motivated to apply the known technique of using a slider mechanism to control the display of specific patent information because it would provide understandable graphics, bookmarks, documents associated with codes and optionally other documents and/or graphics (see Lee Il 95).
Referring to Claim 3, 9, and 17 (substantially similar in scope and language), modified Burns discloses the method of claim 2 and claim 8, and the system of claim 16; The combination of modified Burns and Lee teaches the displaying a plethora of information based on the inputs of users and generating the information in a single display of a plurality of layered information and wherein the second result set is displayed subsequently to the first result set being displayed in response to receiving the second input data via the slider mechanism (see at least Lee: 96 "The global map 2440 includes a time control or time slider control that a user may manipulate. In response to user manipulation, an algorithm may access information germane to a query with respect to time and update the global map graphic accordingly"; see also Lee: ¶ 116 "The user interface2600 allows a user to select a point in time via the time control 2650. A user may manipulate the slider or elect to automate the slider to move backward or forward in time"; see also Lee: ¶ 128 "FIG. 30 is a diagram of an actual time slider 3010 with three rows or columns where the length of the column changes upon placement of a cursor over the timeline 3010"; see also Lee: Claims 16-18).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of using a slider mechanism to control the display of specific patent information (as disclosed by Lee) to the known method and system for managing, analyzing, processing, and presenting intellectual property information wherein the system is capable of displaying a plethora of information based on the inputs of users and generating the information in a single display of a plurality of layered information (as disclosed by modified Burns) to provide understandable graphics, bookmarks, documents associated with codes and optionally other documents and/or graphics. One of ordinary skill in the art would have been motivated to apply the known technique of using a slider mechanism to control the display of specific patent information because it would provide understandable graphics, bookmarks, documents associated with codes and optionally other documents and/or graphics (see Lee Il 95).
Referring to Claim 4 and 10 (substantially similar in scope and language), modified Burns discloses the method of claim 3 and claim 9; The combination of modified Burns and Lee teaches the displaying a plethora of information based on the inputs of users and generating the information in a single display of a plurality of layered information and further comprising receiving third input indicating selection of the first time period and displaying the first result set in response to receiving selection of the first time period (see at least Lee: 1 96 "The global map 2440 includes a time control or time slider control that a user may manipulate. In response to user manipulation, an algorithm may access information germane to a query with respect to time and update the global map graphic accordingly"; see also Lee: ¶ 116 "The user interface 2600 allows a user to select a point in time via the time control 2650. A user may manipulate the slider or elect to automate the slider to move backward or forward in time"; see also Lee: ¶ 128 "FIG. 30 is a diagram of an actual time slider 3010 with three rows or columns where the length of the column changes upon placement of a cursor over the timeline 3010"; see also Lee: Claims 16-18).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of using a slider mechanism to control the display of specific patent information (as disclosed by Lee) to the known method and system for managing, analyzing, processing, and presenting intellectual property information wherein the system is capable of displaying a plethora of information based on the inputs of users and generating the information in a single display of a plurality of layered information (as disclosed by modified Burns) to provide understandable graphics, bookmarks, documents associated with codes and optionally other documents and/or graphics. One of ordinary skill in the art would have been motivated to apply the known technique of using a slider mechanism to control the display of specific patent information because it would provide understandable graphics, bookmarks, documents associated with codes and optionally other documents and/or graphics (see Lee Il 95).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
U.S. Patent Application Publication No. 20180053092 to Hajizadeh discusses a system for management and optimization of innovation. A data mining and clustering module compares a new innovation submission with existing internal and external entries and databases, identifies similarities and groups similar entries together. Intelligent machine learning learns from the available data of previous innovation projects and provide estimates of outputs or target values for new innovation submissions or entries.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/Joshua D Schneider/Examiner, Art Unit 3626
/JESSICA LEMIEUX/Supervisory Patent Examiner, Art Unit 3626
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